/////////////////////////////////////////// // Running convGAN-proximary-full on folding_yeast5 /////////////////////////////////////////// Load 'data_input/folding_yeast5' from pickle file Data loaded. -> Shuffling data ### Start exercise for synthetic point generator ====== Step 1/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 1/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.1601 42/116 [=========>....................] - ETA: 0s - loss: 0.0875  84/116 [====================>.........] - ETA: 0s - loss: 0.0711 116/116 [==============================] - 0s 1ms/step - loss: 0.0701 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1408 41/116 [=========>....................] - ETA: 0s - loss: 0.0572 83/116 [====================>.........] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0594 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0207 41/116 [=========>....................] - ETA: 0s - loss: 0.0714 84/116 [====================>.........] - ETA: 0s - loss: 0.0635 116/116 [==============================] - 0s 1ms/step - loss: 0.0564 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0051 42/116 [=========>....................] - ETA: 0s - loss: 0.0546 83/116 [====================>.........] - ETA: 0s - loss: 0.0441 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0460 42/116 [=========>....................] - ETA: 0s - loss: 0.0527 82/116 [====================>.........] - ETA: 0s - loss: 0.0502 116/116 [==============================] - 0s 1ms/step - loss: 0.0536 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0238 43/116 [==========>...................] - ETA: 0s - loss: 0.0461 82/116 [====================>.........] - ETA: 0s - loss: 0.0500 116/116 [==============================] - ETA: 0s - loss: 0.0533 116/116 [==============================] - 0s 1ms/step - loss: 0.0533 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0185 38/116 [========>.....................] - ETA: 0s - loss: 0.0442 78/116 [===================>..........] - ETA: 0s - loss: 0.0543 115/116 [============================>.] - ETA: 0s - loss: 0.0539 116/116 [==============================] - 0s 1ms/step - loss: 0.0541 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1516 42/116 [=========>....................] - ETA: 0s - loss: 0.0729 77/116 [==================>...........] - ETA: 0s - loss: 0.0622 113/116 [============================>.] - ETA: 0s - loss: 0.0539 116/116 [==============================] - 0s 1ms/step - loss: 0.0546 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1775 39/116 [=========>....................] - ETA: 0s - loss: 0.0500 80/116 [===================>..........] - ETA: 0s - loss: 0.0462 116/116 [==============================] - 0s 1ms/step - loss: 0.0518 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0095 40/116 [=========>....................] - ETA: 0s - loss: 0.0440 79/116 [===================>..........] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 3, 6 GAN f1 score: 0.571 GAN cohens kappa score: 0.556 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 0, 9 LR f1 score: 0.600 LR cohens kappa score: 0.582 LR average precision score: 0.895 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 4, 5 GB f1 score: 0.625 GB cohens kappa score: 0.615 -> test with 'KNN' KNN tn, fp: 280, 8 KNN fn, tp: 0, 9 KNN f1 score: 0.692 KNN cohens kappa score: 0.680 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.1791 42/116 [=========>....................] - ETA: 0s - loss: 0.1450  82/116 [====================>.........] - ETA: 0s - loss: 0.1274 116/116 [==============================] - 0s 1ms/step - loss: 0.1169 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1159 42/116 [=========>....................] - ETA: 0s - loss: 0.0827 80/116 [===================>..........] - ETA: 0s - loss: 0.0739 113/116 [============================>.] - ETA: 0s - loss: 0.0715 116/116 [==============================] - 0s 1ms/step - loss: 0.0726 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 42/116 [=========>....................] - ETA: 0s - loss: 0.0722 83/116 [====================>.........] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0648 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0331 42/116 [=========>....................] - ETA: 0s - loss: 0.0505 83/116 [====================>.........] - ETA: 0s - loss: 0.0635 116/116 [==============================] - 0s 1ms/step - loss: 0.0602 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0043 42/116 [=========>....................] - ETA: 0s - loss: 0.0615 84/116 [====================>.........] - ETA: 0s - loss: 0.0635 116/116 [==============================] - 0s 1ms/step - loss: 0.0609 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0646 42/116 [=========>....................] - ETA: 0s - loss: 0.0456 82/116 [====================>.........] - ETA: 0s - loss: 0.0568 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0787 42/116 [=========>....................] - ETA: 0s - loss: 0.0794 82/116 [====================>.........] - ETA: 0s - loss: 0.0589 116/116 [==============================] - 0s 1ms/step - loss: 0.0546 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0105 42/116 [=========>....................] - ETA: 0s - loss: 0.0403 80/116 [===================>..........] - ETA: 0s - loss: 0.0513 116/116 [==============================] - 0s 1ms/step - loss: 0.0560 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 42/116 [=========>....................] - ETA: 0s - loss: 0.0592 82/116 [====================>.........] - ETA: 0s - loss: 0.0530 116/116 [==============================] - 0s 1ms/step - loss: 0.0531 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0101 42/116 [=========>....................] - ETA: 0s - loss: 0.0508 84/116 [====================>.........] - ETA: 0s - loss: 0.0489 116/116 [==============================] - 0s 1ms/step - loss: 0.0531 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 0, 9 GAN f1 score: 0.600 GAN cohens kappa score: 0.582 -> test with 'LR' LR tn, fp: 273, 15 LR fn, tp: 0, 9 LR f1 score: 0.545 LR cohens kappa score: 0.524 LR average precision score: 0.712 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 0, 9 RF f1 score: 0.857 RF cohens kappa score: 0.852 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 1, 8 GB f1 score: 0.762 GB cohens kappa score: 0.753 -> test with 'KNN' KNN tn, fp: 274, 14 KNN fn, tp: 0, 9 KNN f1 score: 0.562 KNN cohens kappa score: 0.543 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 9.6613e-04 43/116 [==========>...................] - ETA: 0s - loss: 0.0789  85/116 [====================>.........] - ETA: 0s - loss: 0.0643 116/116 [==============================] - 0s 1ms/step - loss: 0.0674 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0026 40/116 [=========>....................] - ETA: 0s - loss: 0.0530 78/116 [===================>..........] - ETA: 0s - loss: 0.0583 116/116 [==============================] - 0s 1ms/step - loss: 0.0594 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0129 42/116 [=========>....................] - ETA: 0s - loss: 0.0592 82/116 [====================>.........] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0569 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0053 42/116 [=========>....................] - ETA: 0s - loss: 0.0486 77/116 [==================>...........] - ETA: 0s - loss: 0.0581 110/116 [===========================>..] - ETA: 0s - loss: 0.0566 116/116 [==============================] - 0s 1ms/step - loss: 0.0545 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0041 37/116 [========>.....................] - ETA: 0s - loss: 0.0319 77/116 [==================>...........] - ETA: 0s - loss: 0.0478 116/116 [==============================] - ETA: 0s - loss: 0.0526 116/116 [==============================] - 0s 1ms/step - loss: 0.0526 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1836 42/116 [=========>....................] - ETA: 0s - loss: 0.0590 81/116 [===================>..........] - ETA: 0s - loss: 0.0549 116/116 [==============================] - 0s 1ms/step - loss: 0.0515 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2397 40/116 [=========>....................] - ETA: 0s - loss: 0.0608 80/116 [===================>..........] - ETA: 0s - loss: 0.0543 116/116 [==============================] - 0s 1ms/step - loss: 0.0512 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0156 41/116 [=========>....................] - ETA: 0s - loss: 0.0245 82/116 [====================>.........] - ETA: 0s - loss: 0.0525 116/116 [==============================] - 0s 1ms/step - loss: 0.0555 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0040 41/116 [=========>....................] - ETA: 0s - loss: 0.0535 83/116 [====================>.........] - ETA: 0s - loss: 0.0517 116/116 [==============================] - 0s 1ms/step - loss: 0.0513 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0038 41/116 [=========>....................] - ETA: 0s - loss: 0.0590 82/116 [====================>.........] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 1ms/step - loss: 0.0489 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 2, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.623 -> test with 'LR' LR tn, fp: 278, 10 LR fn, tp: 0, 9 LR f1 score: 0.643 LR cohens kappa score: 0.628 LR average precision score: 0.612 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 3, 6 RF f1 score: 0.632 RF cohens kappa score: 0.619 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 2, 7 GB f1 score: 0.700 GB cohens kappa score: 0.690 -> test with 'KNN' KNN tn, fp: 279, 9 KNN fn, tp: 1, 8 KNN f1 score: 0.615 KNN cohens kappa score: 0.600 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.0107 42/116 [=========>....................] - ETA: 0s - loss: 0.0498  82/116 [====================>.........] - ETA: 0s - loss: 0.0469 116/116 [==============================] - 0s 1ms/step - loss: 0.0483 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0072 44/116 [==========>...................] - ETA: 0s - loss: 0.0463 85/116 [====================>.........] - ETA: 0s - loss: 0.0400 116/116 [==============================] - 0s 1ms/step - loss: 0.0433 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0024 41/116 [=========>....................] - ETA: 0s - loss: 0.0479 81/116 [===================>..........] - ETA: 0s - loss: 0.0431 116/116 [==============================] - 0s 1ms/step - loss: 0.0420 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 43/116 [==========>...................] - ETA: 0s - loss: 0.0363 84/116 [====================>.........] - ETA: 0s - loss: 0.0384 116/116 [==============================] - 0s 1ms/step - loss: 0.0405 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0155 41/116 [=========>....................] - ETA: 0s - loss: 0.0597 80/116 [===================>..........] - ETA: 0s - loss: 0.0394 116/116 [==============================] - 0s 1ms/step - loss: 0.0417 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0152 40/116 [=========>....................] - ETA: 0s - loss: 0.0324 80/116 [===================>..........] - ETA: 0s - loss: 0.0303 116/116 [==============================] - 0s 1ms/step - loss: 0.0392 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0631 40/116 [=========>....................] - ETA: 0s - loss: 0.0429 81/116 [===================>..........] - ETA: 0s - loss: 0.0387 116/116 [==============================] - 0s 1ms/step - loss: 0.0379 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0019 37/116 [========>.....................] - ETA: 0s - loss: 0.0377 73/116 [=================>............] - ETA: 0s - loss: 0.0427 109/116 [===========================>..] - ETA: 0s - loss: 0.0416 116/116 [==============================] - 0s 1ms/step - loss: 0.0413 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0019 41/116 [=========>....................] - ETA: 0s - loss: 0.0410 80/116 [===================>..........] - ETA: 0s - loss: 0.0382 116/116 [==============================] - ETA: 0s - loss: 0.0378 116/116 [==============================] - 0s 1ms/step - loss: 0.0378 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0014 38/116 [========>.....................] - ETA: 0s - loss: 0.0333 78/116 [===================>..........] - ETA: 0s - loss: 0.0327 116/116 [==============================] - 0s 1ms/step - loss: 0.0397 -> test with GAN.predict GAN tn, fp: 286, 2 GAN fn, tp: 3, 6 GAN f1 score: 0.706 GAN cohens kappa score: 0.697 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 2, 7 LR f1 score: 0.609 LR cohens kappa score: 0.594 LR average precision score: 0.744 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 288, 0 GB fn, tp: 3, 6 GB f1 score: 0.800 GB cohens kappa score: 0.795 -> test with 'KNN' KNN tn, fp: 287, 1 KNN fn, tp: 0, 9 KNN f1 score: 0.947 KNN cohens kappa score: 0.946 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.1722 40/116 [=========>....................] - ETA: 0s - loss: 0.0755  74/116 [==================>...........] - ETA: 0s - loss: 0.0837 113/116 [============================>.] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0733 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0040 27/116 [=====>........................] - ETA: 0s - loss: 0.0860 59/116 [==============>...............] - ETA: 0s - loss: 0.0691 95/116 [=======================>......] - ETA: 0s - loss: 0.0645 116/116 [==============================] - 0s 2ms/step - loss: 0.0672 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 38/116 [========>.....................] - ETA: 0s - loss: 0.0680 79/116 [===================>..........] - ETA: 0s - loss: 0.0595 116/116 [==============================] - 0s 1ms/step - loss: 0.0653 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0670 39/116 [=========>....................] - ETA: 0s - loss: 0.0428 79/116 [===================>..........] - ETA: 0s - loss: 0.0497 116/116 [==============================] - 0s 1ms/step - loss: 0.0609 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0548 41/116 [=========>....................] - ETA: 0s - loss: 0.0632 80/116 [===================>..........] - ETA: 0s - loss: 0.0692 116/116 [==============================] - 0s 1ms/step - loss: 0.0595 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1125 40/116 [=========>....................] - ETA: 0s - loss: 0.0564 79/116 [===================>..........] - ETA: 0s - loss: 0.0591 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2587 39/116 [=========>....................] - ETA: 0s - loss: 0.0620 77/116 [==================>...........] - ETA: 0s - loss: 0.0531 116/116 [==============================] - 0s 1ms/step - loss: 0.0557 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0082 41/116 [=========>....................] - ETA: 0s - loss: 0.0516 81/116 [===================>..........] - ETA: 0s - loss: 0.0628 116/116 [==============================] - 0s 1ms/step - loss: 0.0574 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0247 41/116 [=========>....................] - ETA: 0s - loss: 0.0584 75/116 [==================>...........] - ETA: 0s - loss: 0.0674 114/116 [============================>.] - ETA: 0s - loss: 0.0543 116/116 [==============================] - 0s 1ms/step - loss: 0.0559 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1520 41/116 [=========>....................] - ETA: 0s - loss: 0.0790 81/116 [===================>..........] - ETA: 0s - loss: 0.0625 116/116 [==============================] - 0s 1ms/step - loss: 0.0547 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.600 -> test with 'LR' LR tn, fp: 274, 14 LR fn, tp: 0, 8 LR f1 score: 0.533 LR cohens kappa score: 0.514 LR average precision score: 0.701 -> test with 'RF' RF tn, fp: 282, 6 RF fn, tp: 0, 8 RF f1 score: 0.727 RF cohens kappa score: 0.718 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 0, 8 GB f1 score: 0.762 GB cohens kappa score: 0.754 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.554 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.0422 42/116 [=========>....................] - ETA: 0s - loss: 0.0853  81/116 [===================>..........] - ETA: 0s - loss: 0.0624 116/116 [==============================] - ETA: 0s - loss: 0.0671 116/116 [==============================] - 0s 1ms/step - loss: 0.0671 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0196 36/116 [========>.....................] - ETA: 0s - loss: 0.0471 73/116 [=================>............] - ETA: 0s - loss: 0.0545 109/116 [===========================>..] - ETA: 0s - loss: 0.0544 116/116 [==============================] - 0s 1ms/step - loss: 0.0576 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1241 41/116 [=========>....................] - ETA: 0s - loss: 0.0619 81/116 [===================>..........] - ETA: 0s - loss: 0.0574 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0296 42/116 [=========>....................] - ETA: 0s - loss: 0.0741 82/116 [====================>.........] - ETA: 0s - loss: 0.0591 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0092 41/116 [=========>....................] - ETA: 0s - loss: 0.0679 81/116 [===================>..........] - ETA: 0s - loss: 0.0571 116/116 [==============================] - 0s 1ms/step - loss: 0.0545 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2924 40/116 [=========>....................] - ETA: 0s - loss: 0.0580 80/116 [===================>..........] - ETA: 0s - loss: 0.0396 116/116 [==============================] - 0s 1ms/step - loss: 0.0530 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0968 41/116 [=========>....................] - ETA: 0s - loss: 0.0512 81/116 [===================>..........] - ETA: 0s - loss: 0.0485 116/116 [==============================] - 0s 1ms/step - loss: 0.0538 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0038 40/116 [=========>....................] - ETA: 0s - loss: 0.0470 80/116 [===================>..........] - ETA: 0s - loss: 0.0497 116/116 [==============================] - 0s 1ms/step - loss: 0.0521 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0301 41/116 [=========>....................] - ETA: 0s - loss: 0.0485 80/116 [===================>..........] - ETA: 0s - loss: 0.0514 116/116 [==============================] - 0s 1ms/step - loss: 0.0528 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0135 40/116 [=========>....................] - ETA: 0s - loss: 0.0703 80/116 [===================>..........] - ETA: 0s - loss: 0.0515 116/116 [==============================] - 0s 1ms/step - loss: 0.0508 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 9 GAN f1 score: 0.643 GAN cohens kappa score: 0.628 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 0, 9 LR f1 score: 0.600 LR cohens kappa score: 0.582 LR average precision score: 0.703 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 1, 8 RF f1 score: 0.889 RF cohens kappa score: 0.885 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> test with 'KNN' KNN tn, fp: 279, 9 KNN fn, tp: 0, 9 KNN f1 score: 0.667 KNN cohens kappa score: 0.653 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0626 42/116 [=========>....................] - ETA: 0s - loss: 0.0482  84/116 [====================>.........] - ETA: 0s - loss: 0.0584 116/116 [==============================] - 0s 1ms/step - loss: 0.0617 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 3.7319e-05 39/116 [=========>....................] - ETA: 0s - loss: 0.0561  80/116 [===================>..........] - ETA: 0s - loss: 0.0525 116/116 [==============================] - 0s 1ms/step - loss: 0.0532 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0543 40/116 [=========>....................] - ETA: 0s - loss: 0.0172 75/116 [==================>...........] - ETA: 0s - loss: 0.0464 114/116 [============================>.] - ETA: 0s - loss: 0.0482 116/116 [==============================] - 0s 1ms/step - loss: 0.0478 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2851 35/116 [========>.....................] - ETA: 0s - loss: 0.0678 68/116 [================>.............] - ETA: 0s - loss: 0.0517 103/116 [=========================>....] - ETA: 0s - loss: 0.0465 116/116 [==============================] - 0s 1ms/step - loss: 0.0447 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.4674 41/116 [=========>....................] - ETA: 0s - loss: 0.0572 81/116 [===================>..........] - ETA: 0s - loss: 0.0492 116/116 [==============================] - 0s 1ms/step - loss: 0.0418 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0054 42/116 [=========>....................] - ETA: 0s - loss: 0.0437 83/116 [====================>.........] - ETA: 0s - loss: 0.0440 116/116 [==============================] - 0s 1ms/step - loss: 0.0444 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 4.9670e-04 42/116 [=========>....................] - ETA: 0s - loss: 0.0107  81/116 [===================>..........] - ETA: 0s - loss: 0.0287 116/116 [==============================] - 0s 1ms/step - loss: 0.0407 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0057 42/116 [=========>....................] - ETA: 0s - loss: 0.0441 82/116 [====================>.........] - ETA: 0s - loss: 0.0378 116/116 [==============================] - 0s 1ms/step - loss: 0.0405 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0282 42/116 [=========>....................] - ETA: 0s - loss: 0.0322 82/116 [====================>.........] - ETA: 0s - loss: 0.0377 116/116 [==============================] - 0s 1ms/step - loss: 0.0387 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0022 42/116 [=========>....................] - ETA: 0s - loss: 0.0258 83/116 [====================>.........] - ETA: 0s - loss: 0.0408 116/116 [==============================] - 0s 1ms/step - loss: 0.0391 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 3, 6 GAN f1 score: 0.522 GAN cohens kappa score: 0.503 -> test with 'LR' LR tn, fp: 271, 17 LR fn, tp: 1, 8 LR f1 score: 0.471 LR cohens kappa score: 0.446 LR average precision score: 0.419 -> test with 'RF' RF tn, fp: 280, 8 RF fn, tp: 4, 5 RF f1 score: 0.455 RF cohens kappa score: 0.434 -> test with 'GB' GB tn, fp: 280, 8 GB fn, tp: 6, 3 GB f1 score: 0.300 GB cohens kappa score: 0.276 -> test with 'KNN' KNN tn, fp: 275, 13 KNN fn, tp: 0, 9 KNN f1 score: 0.581 KNN cohens kappa score: 0.562 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0096 41/116 [=========>....................] - ETA: 0s - loss: 0.0875  80/116 [===================>..........] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0668 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0660 40/116 [=========>....................] - ETA: 0s - loss: 0.0442 81/116 [===================>..........] - ETA: 0s - loss: 0.0601 116/116 [==============================] - 0s 1ms/step - loss: 0.0614 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0175 42/116 [=========>....................] - ETA: 0s - loss: 0.0578 81/116 [===================>..........] - ETA: 0s - loss: 0.0556 116/116 [==============================] - 0s 1ms/step - loss: 0.0582 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0012 40/116 [=========>....................] - ETA: 0s - loss: 0.0578 80/116 [===================>..........] - ETA: 0s - loss: 0.0570 116/116 [==============================] - 0s 1ms/step - loss: 0.0568 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0039 42/116 [=========>....................] - ETA: 0s - loss: 0.0633 82/116 [====================>.........] - ETA: 0s - loss: 0.0597 116/116 [==============================] - 0s 1ms/step - loss: 0.0595 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0072 41/116 [=========>....................] - ETA: 0s - loss: 0.0296 80/116 [===================>..........] - ETA: 0s - loss: 0.0499 116/116 [==============================] - 0s 1ms/step - loss: 0.0557 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0949 41/116 [=========>....................] - ETA: 0s - loss: 0.0626 80/116 [===================>..........] - ETA: 0s - loss: 0.0618 116/116 [==============================] - 0s 1ms/step - loss: 0.0571 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0075 41/116 [=========>....................] - ETA: 0s - loss: 0.0567 81/116 [===================>..........] - ETA: 0s - loss: 0.0550 116/116 [==============================] - 0s 1ms/step - loss: 0.0526 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0386 41/116 [=========>....................] - ETA: 0s - loss: 0.0780 81/116 [===================>..........] - ETA: 0s - loss: 0.0590 116/116 [==============================] - 0s 1ms/step - loss: 0.0538 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0036 42/116 [=========>....................] - ETA: 0s - loss: 0.0672 82/116 [====================>.........] - ETA: 0s - loss: 0.0592 116/116 [==============================] - 0s 1ms/step - loss: 0.0529 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 1, 8 GAN f1 score: 0.727 GAN cohens kappa score: 0.717 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 0, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.755 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 2, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 1, 8 GB f1 score: 0.889 GB cohens kappa score: 0.885 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 0, 9 KNN f1 score: 0.783 KNN cohens kappa score: 0.774 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0247 40/116 [=========>....................] - ETA: 0s - loss: 0.0919  81/116 [===================>..........] - ETA: 0s - loss: 0.0871 116/116 [==============================] - 0s 1ms/step - loss: 0.0825 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0186 40/116 [=========>....................] - ETA: 0s - loss: 0.0951 80/116 [===================>..........] - ETA: 0s - loss: 0.0871 116/116 [==============================] - 0s 1ms/step - loss: 0.0823 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 38/116 [========>.....................] - ETA: 0s - loss: 0.0791 79/116 [===================>..........] - ETA: 0s - loss: 0.0698 116/116 [==============================] - 0s 1ms/step - loss: 0.0673 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0327 40/116 [=========>....................] - ETA: 0s - loss: 0.0618 81/116 [===================>..........] - ETA: 0s - loss: 0.0723 116/116 [==============================] - 0s 1ms/step - loss: 0.0607 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0053 41/116 [=========>....................] - ETA: 0s - loss: 0.0498 79/116 [===================>..........] - ETA: 0s - loss: 0.0563 114/116 [============================>.] - ETA: 0s - loss: 0.0606 116/116 [==============================] - 0s 1ms/step - loss: 0.0604 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0340 32/116 [=======>......................] - ETA: 0s - loss: 0.0585 65/116 [===============>..............] - ETA: 0s - loss: 0.0724 96/116 [=======================>......] - ETA: 0s - loss: 0.0626 116/116 [==============================] - 0s 2ms/step - loss: 0.0651 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.3152 32/116 [=======>......................] - ETA: 0s - loss: 0.0701 62/116 [===============>..............] - ETA: 0s - loss: 0.0582 93/116 [=======================>......] - ETA: 0s - loss: 0.0593 116/116 [==============================] - 0s 2ms/step - loss: 0.0589 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0115 34/116 [=======>......................] - ETA: 0s - loss: 0.0511 67/116 [================>.............] - ETA: 0s - loss: 0.0608 97/116 [========================>.....] - ETA: 0s - loss: 0.0618 116/116 [==============================] - 0s 2ms/step - loss: 0.0587 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1020 31/116 [=======>......................] - ETA: 0s - loss: 0.0547 60/116 [==============>...............] - ETA: 0s - loss: 0.0611 93/116 [=======================>......] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 2ms/step - loss: 0.0559 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0019 35/116 [========>.....................] - ETA: 0s - loss: 0.0529 66/116 [================>.............] - ETA: 0s - loss: 0.0533 97/116 [========================>.....] - ETA: 0s - loss: 0.0542 116/116 [==============================] - 0s 2ms/step - loss: 0.0558 -> test with GAN.predict GAN tn, fp: 284, 4 GAN fn, tp: 1, 8 GAN f1 score: 0.762 GAN cohens kappa score: 0.753 -> test with 'LR' LR tn, fp: 273, 15 LR fn, tp: 0, 9 LR f1 score: 0.545 LR cohens kappa score: 0.524 LR average precision score: 0.891 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 1, 8 RF f1 score: 0.800 RF cohens kappa score: 0.793 -> test with 'GB' GB tn, fp: 285, 3 GB fn, tp: 1, 8 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 277, 11 KNN fn, tp: 0, 9 KNN f1 score: 0.621 KNN cohens kappa score: 0.604 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0255 42/116 [=========>....................] - ETA: 0s - loss: 0.0651  82/116 [====================>.........] - ETA: 0s - loss: 0.0768 116/116 [==============================] - 0s 1ms/step - loss: 0.0685 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0012 41/116 [=========>....................] - ETA: 0s - loss: 0.0695 81/116 [===================>..........] - ETA: 0s - loss: 0.0629 116/116 [==============================] - 0s 1ms/step - loss: 0.0624 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0159 40/116 [=========>....................] - ETA: 0s - loss: 0.0612 80/116 [===================>..........] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0118 38/116 [========>.....................] - ETA: 0s - loss: 0.0674 80/116 [===================>..........] - ETA: 0s - loss: 0.0627 116/116 [==============================] - ETA: 0s - loss: 0.0578 116/116 [==============================] - 0s 1ms/step - loss: 0.0578 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0513 42/116 [=========>....................] - ETA: 0s - loss: 0.0488 82/116 [====================>.........] - ETA: 0s - loss: 0.0581 116/116 [==============================] - 0s 1ms/step - loss: 0.0573 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0806 40/116 [=========>....................] - ETA: 0s - loss: 0.0862 81/116 [===================>..........] - ETA: 0s - loss: 0.0613 116/116 [==============================] - 0s 1ms/step - loss: 0.0546 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0118 42/116 [=========>....................] - ETA: 0s - loss: 0.0553 78/116 [===================>..........] - ETA: 0s - loss: 0.0535 116/116 [==============================] - 0s 1ms/step - loss: 0.0535 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0467 41/116 [=========>....................] - ETA: 0s - loss: 0.0533 79/116 [===================>..........] - ETA: 0s - loss: 0.0525 114/116 [============================>.] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0534 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0466 36/116 [========>.....................] - ETA: 0s - loss: 0.0480 74/116 [==================>...........] - ETA: 0s - loss: 0.0589 114/116 [============================>.] - ETA: 0s - loss: 0.0548 116/116 [==============================] - 0s 1ms/step - loss: 0.0543 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.4033 42/116 [=========>....................] - ETA: 0s - loss: 0.0518 83/116 [====================>.........] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0522 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 1, 7 GAN f1 score: 0.700 GAN cohens kappa score: 0.690 -> test with 'LR' LR tn, fp: 278, 10 LR fn, tp: 0, 8 LR f1 score: 0.615 LR cohens kappa score: 0.600 LR average precision score: 0.635 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 3, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 3, 5 GB f1 score: 0.667 GB cohens kappa score: 0.658 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 0, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.718 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0348 41/116 [=========>....................] - ETA: 0s - loss: 0.0663  77/116 [==================>...........] - ETA: 0s - loss: 0.0658 113/116 [============================>.] - ETA: 0s - loss: 0.0716 116/116 [==============================] - 0s 1ms/step - loss: 0.0720 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0467 40/116 [=========>....................] - ETA: 0s - loss: 0.0667 80/116 [===================>..........] - ETA: 0s - loss: 0.0685 116/116 [==============================] - 0s 1ms/step - loss: 0.0637 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0102 40/116 [=========>....................] - ETA: 0s - loss: 0.0524 78/116 [===================>..........] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0620 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0153 40/116 [=========>....................] - ETA: 0s - loss: 0.0653 76/116 [==================>...........] - ETA: 0s - loss: 0.0620 115/116 [============================>.] - ETA: 0s - loss: 0.0606 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0025 39/116 [=========>....................] - ETA: 0s - loss: 0.0569 77/116 [==================>...........] - ETA: 0s - loss: 0.0654 115/116 [============================>.] - ETA: 0s - loss: 0.0625 116/116 [==============================] - 0s 1ms/step - loss: 0.0624 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1033 39/116 [=========>....................] - ETA: 0s - loss: 0.0498 79/116 [===================>..........] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1408 43/116 [==========>...................] - ETA: 0s - loss: 0.0500 82/116 [====================>.........] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0600 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.3535 41/116 [=========>....................] - ETA: 0s - loss: 0.0541 81/116 [===================>..........] - ETA: 0s - loss: 0.0579 116/116 [==============================] - 0s 1ms/step - loss: 0.0565 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1110 40/116 [=========>....................] - ETA: 0s - loss: 0.0578 80/116 [===================>..........] - ETA: 0s - loss: 0.0530 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0033 41/116 [=========>....................] - ETA: 0s - loss: 0.0449 81/116 [===================>..........] - ETA: 0s - loss: 0.0545 116/116 [==============================] - 0s 1ms/step - loss: 0.0561 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 1, 8 GAN f1 score: 0.552 GAN cohens kappa score: 0.532 -> test with 'LR' LR tn, fp: 272, 16 LR fn, tp: 0, 9 LR f1 score: 0.529 LR cohens kappa score: 0.507 LR average precision score: 0.668 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 3, 6 RF f1 score: 0.667 RF cohens kappa score: 0.656 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 2, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 274, 14 KNN fn, tp: 0, 9 KNN f1 score: 0.562 KNN cohens kappa score: 0.543 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 8.2898e-04 41/116 [=========>....................] - ETA: 0s - loss: 0.0473  79/116 [===================>..........] - ETA: 0s - loss: 0.0515 116/116 [==============================] - 0s 1ms/step - loss: 0.0509 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0040 38/116 [========>.....................] - ETA: 0s - loss: 0.0277 77/116 [==================>...........] - ETA: 0s - loss: 0.0363 116/116 [==============================] - ETA: 0s - loss: 0.0489 116/116 [==============================] - 0s 1ms/step - loss: 0.0489 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0010 40/116 [=========>....................] - ETA: 0s - loss: 0.0423 79/116 [===================>..........] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0466 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0539 42/116 [=========>....................] - ETA: 0s - loss: 0.0441 83/116 [====================>.........] - ETA: 0s - loss: 0.0445 116/116 [==============================] - 0s 1ms/step - loss: 0.0449 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0796 41/116 [=========>....................] - ETA: 0s - loss: 0.0502 78/116 [===================>..........] - ETA: 0s - loss: 0.0502 116/116 [==============================] - 0s 1ms/step - loss: 0.0462 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0140 39/116 [=========>....................] - ETA: 0s - loss: 0.0491 76/116 [==================>...........] - ETA: 0s - loss: 0.0430 108/116 [==========================>...] - ETA: 0s - loss: 0.0386 116/116 [==============================] - 0s 1ms/step - loss: 0.0436 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0129 33/116 [=======>......................] - ETA: 0s - loss: 0.0338 64/116 [===============>..............] - ETA: 0s - loss: 0.0376 102/116 [=========================>....] - ETA: 0s - loss: 0.0419 116/116 [==============================] - 0s 1ms/step - loss: 0.0440 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0097 41/116 [=========>....................] - ETA: 0s - loss: 0.0331 80/116 [===================>..........] - ETA: 0s - loss: 0.0369 116/116 [==============================] - 0s 1ms/step - loss: 0.0441 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 41/116 [=========>....................] - ETA: 0s - loss: 0.0364 82/116 [====================>.........] - ETA: 0s - loss: 0.0456 116/116 [==============================] - 0s 1ms/step - loss: 0.0434 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0844 40/116 [=========>....................] - ETA: 0s - loss: 0.0385 78/116 [===================>..........] - ETA: 0s - loss: 0.0392 116/116 [==============================] - ETA: 0s - loss: 0.0438 116/116 [==============================] - 0s 1ms/step - loss: 0.0438 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 1, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.625 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 0, 9 LR f1 score: 0.600 LR cohens kappa score: 0.582 LR average precision score: 0.701 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 2, 7 RF f1 score: 0.737 RF cohens kappa score: 0.728 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 2, 7 GB f1 score: 0.667 GB cohens kappa score: 0.655 -> test with 'KNN' KNN tn, fp: 277, 11 KNN fn, tp: 0, 9 KNN f1 score: 0.621 KNN cohens kappa score: 0.604 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0060 41/116 [=========>....................] - ETA: 0s - loss: 0.0751  81/116 [===================>..........] - ETA: 0s - loss: 0.0735 116/116 [==============================] - 0s 1ms/step - loss: 0.0758 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 42/116 [=========>....................] - ETA: 0s - loss: 0.0656 82/116 [====================>.........] - ETA: 0s - loss: 0.0686 116/116 [==============================] - 0s 1ms/step - loss: 0.0669 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0220 41/116 [=========>....................] - ETA: 0s - loss: 0.0495 81/116 [===================>..........] - ETA: 0s - loss: 0.0655 116/116 [==============================] - 0s 1ms/step - loss: 0.0662 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0287 41/116 [=========>....................] - ETA: 0s - loss: 0.0478 82/116 [====================>.........] - ETA: 0s - loss: 0.0618 116/116 [==============================] - 0s 1ms/step - loss: 0.0635 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1033 42/116 [=========>....................] - ETA: 0s - loss: 0.0666 83/116 [====================>.........] - ETA: 0s - loss: 0.0608 116/116 [==============================] - 0s 1ms/step - loss: 0.0622 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0595 41/116 [=========>....................] - ETA: 0s - loss: 0.0750 78/116 [===================>..........] - ETA: 0s - loss: 0.0687 116/116 [==============================] - 0s 1ms/step - loss: 0.0647 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0149 37/116 [========>.....................] - ETA: 0s - loss: 0.0475 74/116 [==================>...........] - ETA: 0s - loss: 0.0596 109/116 [===========================>..] - ETA: 0s - loss: 0.0617 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0335 38/116 [========>.....................] - ETA: 0s - loss: 0.0432 76/116 [==================>...........] - ETA: 0s - loss: 0.0576 113/116 [============================>.] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0619 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0499 36/116 [========>.....................] - ETA: 0s - loss: 0.0618 73/116 [=================>............] - ETA: 0s - loss: 0.0625 111/116 [===========================>..] - ETA: 0s - loss: 0.0580 116/116 [==============================] - 0s 1ms/step - loss: 0.0589 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0263 36/116 [========>.....................] - ETA: 0s - loss: 0.0562 73/116 [=================>............] - ETA: 0s - loss: 0.0598 109/116 [===========================>..] - ETA: 0s - loss: 0.0544 116/116 [==============================] - 0s 1ms/step - loss: 0.0591 -> test with GAN.predict GAN tn, fp: 281, 7 GAN fn, tp: 2, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.594 -> test with 'LR' LR tn, fp: 280, 8 LR fn, tp: 0, 9 LR f1 score: 0.692 LR cohens kappa score: 0.680 LR average precision score: 0.835 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 1, 8 RF f1 score: 0.889 RF cohens kappa score: 0.885 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 2, 7 GB f1 score: 0.824 GB cohens kappa score: 0.818 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 0, 9 KNN f1 score: 0.783 KNN cohens kappa score: 0.774 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.7578 41/116 [=========>....................] - ETA: 0s - loss: 0.1472  82/116 [====================>.........] - ETA: 0s - loss: 0.1410 116/116 [==============================] - 0s 1ms/step - loss: 0.1191 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0091 42/116 [=========>....................] - ETA: 0s - loss: 0.0873 83/116 [====================>.........] - ETA: 0s - loss: 0.0875 116/116 [==============================] - 0s 1ms/step - loss: 0.0869 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 4.2562e-04 42/116 [=========>....................] - ETA: 0s - loss: 0.1048  81/116 [===================>..........] - ETA: 0s - loss: 0.0852 116/116 [==============================] - 0s 1ms/step - loss: 0.0729 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0043 42/116 [=========>....................] - ETA: 0s - loss: 0.0622 83/116 [====================>.........] - ETA: 0s - loss: 0.0660 116/116 [==============================] - 0s 1ms/step - loss: 0.0661 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0605 42/116 [=========>....................] - ETA: 0s - loss: 0.0574 82/116 [====================>.........] - ETA: 0s - loss: 0.0673 116/116 [==============================] - 0s 1ms/step - loss: 0.0635 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0199 42/116 [=========>....................] - ETA: 0s - loss: 0.0665 84/116 [====================>.........] - ETA: 0s - loss: 0.0547 116/116 [==============================] - 0s 1ms/step - loss: 0.0603 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0037 37/116 [========>.....................] - ETA: 0s - loss: 0.0449 71/116 [=================>............] - ETA: 0s - loss: 0.0572 103/116 [=========================>....] - ETA: 0s - loss: 0.0620 116/116 [==============================] - 0s 1ms/step - loss: 0.0592 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.3106 42/116 [=========>....................] - ETA: 0s - loss: 0.0581 82/116 [====================>.........] - ETA: 0s - loss: 0.0552 116/116 [==============================] - 0s 1ms/step - loss: 0.0569 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0038 41/116 [=========>....................] - ETA: 0s - loss: 0.0494 82/116 [====================>.........] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0200 41/116 [=========>....................] - ETA: 0s - loss: 0.0495 82/116 [====================>.........] - ETA: 0s - loss: 0.0569 116/116 [==============================] - 0s 1ms/step - loss: 0.0569 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 3, 6 GAN f1 score: 0.667 GAN cohens kappa score: 0.656 -> test with 'LR' LR tn, fp: 279, 9 LR fn, tp: 0, 9 LR f1 score: 0.667 LR cohens kappa score: 0.653 LR average precision score: 0.738 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 5, 4 GB f1 score: 0.533 GB cohens kappa score: 0.522 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 1, 8 KNN f1 score: 0.696 KNN cohens kappa score: 0.684 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0055 39/116 [=========>....................] - ETA: 0s - loss: 0.0500  77/116 [==================>...........] - ETA: 0s - loss: 0.0641 111/116 [===========================>..] - ETA: 0s - loss: 0.0723 116/116 [==============================] - 0s 1ms/step - loss: 0.0720 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 37/116 [========>.....................] - ETA: 0s - loss: 0.0849 73/116 [=================>............] - ETA: 0s - loss: 0.0617 110/116 [===========================>..] - ETA: 0s - loss: 0.0568 116/116 [==============================] - 0s 1ms/step - loss: 0.0594 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0576 35/116 [========>.....................] - ETA: 0s - loss: 0.0660 70/116 [=================>............] - ETA: 0s - loss: 0.0558 106/116 [==========================>...] - ETA: 0s - loss: 0.0544 116/116 [==============================] - 0s 1ms/step - loss: 0.0529 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1772 39/116 [=========>....................] - ETA: 0s - loss: 0.0636 78/116 [===================>..........] - ETA: 0s - loss: 0.0569 116/116 [==============================] - ETA: 0s - loss: 0.0516 116/116 [==============================] - 0s 1ms/step - loss: 0.0516 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0189 36/116 [========>.....................] - ETA: 0s - loss: 0.0603 71/116 [=================>............] - ETA: 0s - loss: 0.0547 106/116 [==========================>...] - ETA: 0s - loss: 0.0556 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0050 38/116 [========>.....................] - ETA: 0s - loss: 0.0377 73/116 [=================>............] - ETA: 0s - loss: 0.0546 108/116 [==========================>...] - ETA: 0s - loss: 0.0510 116/116 [==============================] - 0s 1ms/step - loss: 0.0504 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0201 34/116 [=======>......................] - ETA: 0s - loss: 0.0583 72/116 [=================>............] - ETA: 0s - loss: 0.0515 106/116 [==========================>...] - ETA: 0s - loss: 0.0510 116/116 [==============================] - 0s 1ms/step - loss: 0.0504 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0035 31/116 [=======>......................] - ETA: 0s - loss: 0.0494 60/116 [==============>...............] - ETA: 0s - loss: 0.0505 93/116 [=======================>......] - ETA: 0s - loss: 0.0549 116/116 [==============================] - 0s 2ms/step - loss: 0.0517 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1998 37/116 [========>.....................] - ETA: 0s - loss: 0.0598 72/116 [=================>............] - ETA: 0s - loss: 0.0542 107/116 [==========================>...] - ETA: 0s - loss: 0.0500 116/116 [==============================] - 0s 1ms/step - loss: 0.0480 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0055 35/116 [========>.....................] - ETA: 0s - loss: 0.0444 70/116 [=================>............] - ETA: 0s - loss: 0.0417 106/116 [==========================>...] - ETA: 0s - loss: 0.0502 116/116 [==============================] - 0s 1ms/step - loss: 0.0494 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.600 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 0, 8 LR f1 score: 0.552 LR cohens kappa score: 0.533 LR average precision score: 0.387 -> test with 'RF' RF tn, fp: 283, 5 RF fn, tp: 1, 7 RF f1 score: 0.700 RF cohens kappa score: 0.690 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 1, 7 GB f1 score: 0.700 GB cohens kappa score: 0.690 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.554 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 3.0308e-05 41/116 [=========>....................] - ETA: 0s - loss: 0.1005  83/116 [====================>.........] - ETA: 0s - loss: 0.1072 116/116 [==============================] - 0s 1ms/step - loss: 0.1018 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.8588 42/116 [=========>....................] - ETA: 0s - loss: 0.1164 83/116 [====================>.........] - ETA: 0s - loss: 0.0861 116/116 [==============================] - 0s 1ms/step - loss: 0.0810 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0367 40/116 [=========>....................] - ETA: 0s - loss: 0.0286 80/116 [===================>..........] - ETA: 0s - loss: 0.0544 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.4283 42/116 [=========>....................] - ETA: 0s - loss: 0.0523 83/116 [====================>.........] - ETA: 0s - loss: 0.0662 116/116 [==============================] - 0s 1ms/step - loss: 0.0617 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0026 41/116 [=========>....................] - ETA: 0s - loss: 0.0390 82/116 [====================>.........] - ETA: 0s - loss: 0.0593 116/116 [==============================] - 0s 1ms/step - loss: 0.0583 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1007 43/116 [==========>...................] - ETA: 0s - loss: 0.0685 83/116 [====================>.........] - ETA: 0s - loss: 0.0645 116/116 [==============================] - 0s 1ms/step - loss: 0.0552 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0060 42/116 [=========>....................] - ETA: 0s - loss: 0.0476 84/116 [====================>.........] - ETA: 0s - loss: 0.0556 116/116 [==============================] - 0s 1ms/step - loss: 0.0534 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0487 42/116 [=========>....................] - ETA: 0s - loss: 0.0517 82/116 [====================>.........] - ETA: 0s - loss: 0.0518 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0051 43/116 [==========>...................] - ETA: 0s - loss: 0.0435 83/116 [====================>.........] - ETA: 0s - loss: 0.0520 116/116 [==============================] - 0s 1ms/step - loss: 0.0527 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0067 41/116 [=========>....................] - ETA: 0s - loss: 0.0509 81/116 [===================>..........] - ETA: 0s - loss: 0.0512 116/116 [==============================] - 0s 1ms/step - loss: 0.0529 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 1, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.625 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 1, 8 LR f1 score: 0.533 LR cohens kappa score: 0.513 LR average precision score: 0.742 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 2, 7 RF f1 score: 0.700 RF cohens kappa score: 0.690 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 1, 8 GB f1 score: 0.762 GB cohens kappa score: 0.753 -> test with 'KNN' KNN tn, fp: 275, 13 KNN fn, tp: 0, 9 KNN f1 score: 0.581 KNN cohens kappa score: 0.562 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.0055 38/116 [========>.....................] - ETA: 0s - loss: 0.0691  73/116 [=================>............] - ETA: 0s - loss: 0.0979 108/116 [==========================>...] - ETA: 0s - loss: 0.1168 116/116 [==============================] - 0s 1ms/step - loss: 0.1152 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0011 37/116 [========>.....................] - ETA: 0s - loss: 0.0867 72/116 [=================>............] - ETA: 0s - loss: 0.1003 107/116 [==========================>...] - ETA: 0s - loss: 0.0886 116/116 [==============================] - 0s 1ms/step - loss: 0.0861 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 6.9561e-04 36/116 [========>.....................] - ETA: 0s - loss: 0.0677  70/116 [=================>............] - ETA: 0s - loss: 0.0616 104/116 [=========================>....] - ETA: 0s - loss: 0.0673 116/116 [==============================] - 0s 1ms/step - loss: 0.0782 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0201 37/116 [========>.....................] - ETA: 0s - loss: 0.0342 72/116 [=================>............] - ETA: 0s - loss: 0.0421 105/116 [==========================>...] - ETA: 0s - loss: 0.0734 116/116 [==============================] - 0s 1ms/step - loss: 0.0698 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0087 35/116 [========>.....................] - ETA: 0s - loss: 0.0855 69/116 [================>.............] - ETA: 0s - loss: 0.0689 103/116 [=========================>....] - ETA: 0s - loss: 0.0675 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0036 39/116 [=========>....................] - ETA: 0s - loss: 0.0778 72/116 [=================>............] - ETA: 0s - loss: 0.0614 107/116 [==========================>...] - ETA: 0s - loss: 0.0685 116/116 [==============================] - 0s 1ms/step - loss: 0.0667 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 6.5567e-04 36/116 [========>.....................] - ETA: 0s - loss: 0.0661  72/116 [=================>............] - ETA: 0s - loss: 0.0571 105/116 [==========================>...] - ETA: 0s - loss: 0.0592 116/116 [==============================] - 0s 1ms/step - loss: 0.0593 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0304 36/116 [========>.....................] - ETA: 0s - loss: 0.0532 72/116 [=================>............] - ETA: 0s - loss: 0.0609 102/116 [=========================>....] - ETA: 0s - loss: 0.0559 116/116 [==============================] - 0s 2ms/step - loss: 0.0570 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.4278 35/116 [========>.....................] - ETA: 0s - loss: 0.0446 73/116 [=================>............] - ETA: 0s - loss: 0.0498 112/116 [===========================>..] - ETA: 0s - loss: 0.0560 116/116 [==============================] - 0s 1ms/step - loss: 0.0546 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 35/116 [========>.....................] - ETA: 0s - loss: 0.0523 67/116 [================>.............] - ETA: 0s - loss: 0.0633 98/116 [========================>.....] - ETA: 0s - loss: 0.0546 116/116 [==============================] - 0s 2ms/step - loss: 0.0536 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 2, 7 GAN f1 score: 0.583 GAN cohens kappa score: 0.567 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 2, 7 LR f1 score: 0.500 LR cohens kappa score: 0.479 LR average precision score: 0.633 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 2, 7 RF f1 score: 0.824 RF cohens kappa score: 0.818 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 2, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 0, 9 KNN f1 score: 0.720 KNN cohens kappa score: 0.709 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0049 34/116 [=======>......................] - ETA: 0s - loss: 0.1160  68/116 [================>.............] - ETA: 0s - loss: 0.0934 102/116 [=========================>....] - ETA: 0s - loss: 0.0984 116/116 [==============================] - 0s 1ms/step - loss: 0.0982 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 5.5017e-04 40/116 [=========>....................] - ETA: 0s - loss: 0.0290  79/116 [===================>..........] - ETA: 0s - loss: 0.0803 116/116 [==============================] - ETA: 0s - loss: 0.0848 116/116 [==============================] - 0s 1ms/step - loss: 0.0848 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0304 39/116 [=========>....................] - ETA: 0s - loss: 0.0465 78/116 [===================>..........] - ETA: 0s - loss: 0.0482 116/116 [==============================] - ETA: 0s - loss: 0.0672 116/116 [==============================] - 0s 1ms/step - loss: 0.0672 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0016 39/116 [=========>....................] - ETA: 0s - loss: 0.0706 77/116 [==================>...........] - ETA: 0s - loss: 0.0681 115/116 [============================>.] - ETA: 0s - loss: 0.0605 116/116 [==============================] - 0s 1ms/step - loss: 0.0604 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0027 41/116 [=========>....................] - ETA: 0s - loss: 0.0514 80/116 [===================>..........] - ETA: 0s - loss: 0.0538 116/116 [==============================] - 0s 1ms/step - loss: 0.0582 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1179 42/116 [=========>....................] - ETA: 0s - loss: 0.0553 80/116 [===================>..........] - ETA: 0s - loss: 0.0584 116/116 [==============================] - 0s 1ms/step - loss: 0.0547 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0035 39/116 [=========>....................] - ETA: 0s - loss: 0.0331 78/116 [===================>..........] - ETA: 0s - loss: 0.0511 116/116 [==============================] - 0s 1ms/step - loss: 0.0512 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0088 37/116 [========>.....................] - ETA: 0s - loss: 0.0694 75/116 [==================>...........] - ETA: 0s - loss: 0.0609 113/116 [============================>.] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0522 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0285 40/116 [=========>....................] - ETA: 0s - loss: 0.0465 78/116 [===================>..........] - ETA: 0s - loss: 0.0458 116/116 [==============================] - 0s 1ms/step - loss: 0.0508 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2290 39/116 [=========>....................] - ETA: 0s - loss: 0.0554 81/116 [===================>..........] - ETA: 0s - loss: 0.0490 116/116 [==============================] - 0s 1ms/step - loss: 0.0505 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 3, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.480 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.654 LR average precision score: 0.725 -> test with 'RF' RF tn, fp: 283, 5 RF fn, tp: 4, 5 RF f1 score: 0.526 RF cohens kappa score: 0.511 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 4, 5 GB f1 score: 0.526 GB cohens kappa score: 0.511 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 3, 6 KNN f1 score: 0.545 KNN cohens kappa score: 0.529 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 9.7114e-04 37/116 [========>.....................] - ETA: 0s - loss: 0.0991  71/116 [=================>............] - ETA: 0s - loss: 0.1122 103/116 [=========================>....] - ETA: 0s - loss: 0.1067 116/116 [==============================] - 0s 1ms/step - loss: 0.1028 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0041 38/116 [========>.....................] - ETA: 0s - loss: 0.0586 74/116 [==================>...........] - ETA: 0s - loss: 0.0570 111/116 [===========================>..] - ETA: 0s - loss: 0.0851 116/116 [==============================] - 0s 1ms/step - loss: 0.0869 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.4952 39/116 [=========>....................] - ETA: 0s - loss: 0.0731 76/116 [==================>...........] - ETA: 0s - loss: 0.0662 112/116 [===========================>..] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0687 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 6.1515e-04 38/116 [========>.....................] - ETA: 0s - loss: 0.1033  75/116 [==================>...........] - ETA: 0s - loss: 0.0810 112/116 [===========================>..] - ETA: 0s - loss: 0.0671 116/116 [==============================] - 0s 1ms/step - loss: 0.0654 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.3281 40/116 [=========>....................] - ETA: 0s - loss: 0.0455 78/116 [===================>..........] - ETA: 0s - loss: 0.0482 113/116 [============================>.] - ETA: 0s - loss: 0.0589 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0036 40/116 [=========>....................] - ETA: 0s - loss: 0.0716 79/116 [===================>..........] - ETA: 0s - loss: 0.0590 116/116 [==============================] - ETA: 0s - loss: 0.0569 116/116 [==============================] - 0s 1ms/step - loss: 0.0569 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2892 38/116 [========>.....................] - ETA: 0s - loss: 0.0608 75/116 [==================>...........] - ETA: 0s - loss: 0.0554 113/116 [============================>.] - ETA: 0s - loss: 0.0548 116/116 [==============================] - 0s 1ms/step - loss: 0.0539 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0160 40/116 [=========>....................] - ETA: 0s - loss: 0.0528 78/116 [===================>..........] - ETA: 0s - loss: 0.0548 113/116 [============================>.] - ETA: 0s - loss: 0.0522 116/116 [==============================] - 0s 1ms/step - loss: 0.0530 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1641 36/116 [========>.....................] - ETA: 0s - loss: 0.0455 73/116 [=================>............] - ETA: 0s - loss: 0.0553 112/116 [===========================>..] - ETA: 0s - loss: 0.0515 116/116 [==============================] - 0s 1ms/step - loss: 0.0517 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1451 39/116 [=========>....................] - ETA: 0s - loss: 0.0260 77/116 [==================>...........] - ETA: 0s - loss: 0.0451 115/116 [============================>.] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0527 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 2, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.623 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.696 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 5, 4 RF f1 score: 0.615 RF cohens kappa score: 0.608 -> test with 'GB' GB tn, fp: 288, 0 GB fn, tp: 3, 6 GB f1 score: 0.800 GB cohens kappa score: 0.795 -> test with 'KNN' KNN tn, fp: 285, 3 KNN fn, tp: 1, 8 KNN f1 score: 0.800 KNN cohens kappa score: 0.793 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.1764 41/116 [=========>....................] - ETA: 0s - loss: 0.1014  80/116 [===================>..........] - ETA: 0s - loss: 0.0899 116/116 [==============================] - 0s 1ms/step - loss: 0.0804 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0128 39/116 [=========>....................] - ETA: 0s - loss: 0.0899 77/116 [==================>...........] - ETA: 0s - loss: 0.0707 110/116 [===========================>..] - ETA: 0s - loss: 0.0731 116/116 [==============================] - 0s 1ms/step - loss: 0.0717 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 6.9947e-04 34/116 [=======>......................] - ETA: 0s - loss: 0.0689  68/116 [================>.............] - ETA: 0s - loss: 0.0668 107/116 [==========================>...] - ETA: 0s - loss: 0.0650 116/116 [==============================] - 0s 1ms/step - loss: 0.0653 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0993 41/116 [=========>....................] - ETA: 0s - loss: 0.0837 80/116 [===================>..........] - ETA: 0s - loss: 0.0670 113/116 [============================>.] - ETA: 0s - loss: 0.0616 116/116 [==============================] - 0s 1ms/step - loss: 0.0639 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0092 37/116 [========>.....................] - ETA: 0s - loss: 0.0644 73/116 [=================>............] - ETA: 0s - loss: 0.0529 112/116 [===========================>..] - ETA: 0s - loss: 0.0566 116/116 [==============================] - 0s 1ms/step - loss: 0.0608 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0019 41/116 [=========>....................] - ETA: 0s - loss: 0.0747 80/116 [===================>..........] - ETA: 0s - loss: 0.0606 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 40/116 [=========>....................] - ETA: 0s - loss: 0.0777 80/116 [===================>..........] - ETA: 0s - loss: 0.0624 116/116 [==============================] - 0s 1ms/step - loss: 0.0574 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0028 41/116 [=========>....................] - ETA: 0s - loss: 0.0593 80/116 [===================>..........] - ETA: 0s - loss: 0.0662 116/116 [==============================] - 0s 1ms/step - loss: 0.0563 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0087 38/116 [========>.....................] - ETA: 0s - loss: 0.0390 72/116 [=================>............] - ETA: 0s - loss: 0.0540 111/116 [===========================>..] - ETA: 0s - loss: 0.0554 116/116 [==============================] - 0s 1ms/step - loss: 0.0572 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0144 41/116 [=========>....................] - ETA: 0s - loss: 0.0584 80/116 [===================>..........] - ETA: 0s - loss: 0.0570 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 0, 8 GAN f1 score: 0.842 GAN cohens kappa score: 0.837 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 0, 8 LR f1 score: 0.571 LR cohens kappa score: 0.554 LR average precision score: 0.754 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 1, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 -> test with 'GB' GB tn, fp: 285, 3 GB fn, tp: 1, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 274, 14 KNN fn, tp: 0, 8 KNN f1 score: 0.533 KNN cohens kappa score: 0.514 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0466 41/116 [=========>....................] - ETA: 0s - loss: 0.0891  80/116 [===================>..........] - ETA: 0s - loss: 0.0658 116/116 [==============================] - 0s 1ms/step - loss: 0.0627 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0266 40/116 [=========>....................] - ETA: 0s - loss: 0.0720 78/116 [===================>..........] - ETA: 0s - loss: 0.0696 113/116 [============================>.] - ETA: 0s - loss: 0.0581 116/116 [==============================] - 0s 1ms/step - loss: 0.0571 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0033 38/116 [========>.....................] - ETA: 0s - loss: 0.0726 72/116 [=================>............] - ETA: 0s - loss: 0.0666 106/116 [==========================>...] - ETA: 0s - loss: 0.0668 116/116 [==============================] - 0s 1ms/step - loss: 0.0626 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0020 35/116 [========>.....................] - ETA: 0s - loss: 0.0684 72/116 [=================>............] - ETA: 0s - loss: 0.0630 109/116 [===========================>..] - ETA: 0s - loss: 0.0507 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0305 38/116 [========>.....................] - ETA: 0s - loss: 0.0695 77/116 [==================>...........] - ETA: 0s - loss: 0.0670 114/116 [============================>.] - ETA: 0s - loss: 0.0536 116/116 [==============================] - 0s 1ms/step - loss: 0.0532 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0011 37/116 [========>.....................] - ETA: 0s - loss: 0.0668 74/116 [==================>...........] - ETA: 0s - loss: 0.0567 107/116 [==========================>...] - ETA: 0s - loss: 0.0555 116/116 [==============================] - 0s 1ms/step - loss: 0.0538 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0023 36/116 [========>.....................] - ETA: 0s - loss: 0.0266 72/116 [=================>............] - ETA: 0s - loss: 0.0546 111/116 [===========================>..] - ETA: 0s - loss: 0.0505 116/116 [==============================] - 0s 1ms/step - loss: 0.0517 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 39/116 [=========>....................] - ETA: 0s - loss: 0.0364 75/116 [==================>...........] - ETA: 0s - loss: 0.0474 113/116 [============================>.] - ETA: 0s - loss: 0.0509 116/116 [==============================] - 0s 1ms/step - loss: 0.0503 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0346 39/116 [=========>....................] - ETA: 0s - loss: 0.0448 77/116 [==================>...........] - ETA: 0s - loss: 0.0411 115/116 [============================>.] - ETA: 0s - loss: 0.0487 116/116 [==============================] - 0s 1ms/step - loss: 0.0486 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0067 39/116 [=========>....................] - ETA: 0s - loss: 0.0657 76/116 [==================>...........] - ETA: 0s - loss: 0.0501 112/116 [===========================>..] - ETA: 0s - loss: 0.0489 116/116 [==============================] - 0s 1ms/step - loss: 0.0485 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 0, 9 GAN f1 score: 0.667 GAN cohens kappa score: 0.653 -> test with 'LR' LR tn, fp: 272, 16 LR fn, tp: 0, 9 LR f1 score: 0.529 LR cohens kappa score: 0.507 LR average precision score: 0.716 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 1, 8 RF f1 score: 0.800 RF cohens kappa score: 0.793 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 1, 8 GB f1 score: 0.762 GB cohens kappa score: 0.753 -> test with 'KNN' KNN tn, fp: 273, 15 KNN fn, tp: 0, 9 KNN f1 score: 0.545 KNN cohens kappa score: 0.524 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0690 40/116 [=========>....................] - ETA: 0s - loss: 0.0508  79/116 [===================>..........] - ETA: 0s - loss: 0.0552 116/116 [==============================] - 0s 1ms/step - loss: 0.0557 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0264 40/116 [=========>....................] - ETA: 0s - loss: 0.0662 77/116 [==================>...........] - ETA: 0s - loss: 0.0554 116/116 [==============================] - 0s 1ms/step - loss: 0.0535 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0176 39/116 [=========>....................] - ETA: 0s - loss: 0.0637 75/116 [==================>...........] - ETA: 0s - loss: 0.0634 109/116 [===========================>..] - ETA: 0s - loss: 0.0548 116/116 [==============================] - 0s 1ms/step - loss: 0.0522 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0106 38/116 [========>.....................] - ETA: 0s - loss: 0.0359 73/116 [=================>............] - ETA: 0s - loss: 0.0385 111/116 [===========================>..] - ETA: 0s - loss: 0.0506 116/116 [==============================] - 0s 1ms/step - loss: 0.0498 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0029 39/116 [=========>....................] - ETA: 0s - loss: 0.0453 77/116 [==================>...........] - ETA: 0s - loss: 0.0456 115/116 [============================>.] - ETA: 0s - loss: 0.0481 116/116 [==============================] - 0s 1ms/step - loss: 0.0482 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1185 38/116 [========>.....................] - ETA: 0s - loss: 0.0652 75/116 [==================>...........] - ETA: 0s - loss: 0.0588 114/116 [============================>.] - ETA: 0s - loss: 0.0481 116/116 [==============================] - 0s 1ms/step - loss: 0.0476 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0393 39/116 [=========>....................] - ETA: 0s - loss: 0.0482 77/116 [==================>...........] - ETA: 0s - loss: 0.0517 115/116 [============================>.] - ETA: 0s - loss: 0.0480 116/116 [==============================] - 0s 1ms/step - loss: 0.0479 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1033 39/116 [=========>....................] - ETA: 0s - loss: 0.0519 77/116 [==================>...........] - ETA: 0s - loss: 0.0512 115/116 [============================>.] - ETA: 0s - loss: 0.0495 116/116 [==============================] - 0s 1ms/step - loss: 0.0494 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0458 39/116 [=========>....................] - ETA: 0s - loss: 0.0419 78/116 [===================>..........] - ETA: 0s - loss: 0.0412 116/116 [==============================] - 0s 1ms/step - loss: 0.0457 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.3206 41/116 [=========>....................] - ETA: 0s - loss: 0.0630 75/116 [==================>...........] - ETA: 0s - loss: 0.0509 106/116 [==========================>...] - ETA: 0s - loss: 0.0480 116/116 [==============================] - 0s 1ms/step - loss: 0.0475 -> test with GAN.predict GAN tn, fp: 284, 4 GAN fn, tp: 3, 6 GAN f1 score: 0.632 GAN cohens kappa score: 0.619 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 0, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.796 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 3, 6 RF f1 score: 0.750 RF cohens kappa score: 0.743 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 4, 5 GB f1 score: 0.667 GB cohens kappa score: 0.658 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 1, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.717 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0786 40/116 [=========>....................] - ETA: 0s - loss: 0.0865  77/116 [==================>...........] - ETA: 0s - loss: 0.0743 115/116 [============================>.] - ETA: 0s - loss: 0.0688 116/116 [==============================] - 0s 1ms/step - loss: 0.0687 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0030 38/116 [========>.....................] - ETA: 0s - loss: 0.0659 77/116 [==================>...........] - ETA: 0s - loss: 0.0609 113/116 [============================>.] - ETA: 0s - loss: 0.0639 116/116 [==============================] - 0s 1ms/step - loss: 0.0629 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0143 33/116 [=======>......................] - ETA: 0s - loss: 0.0465 66/116 [================>.............] - ETA: 0s - loss: 0.0485 100/116 [========================>.....] - ETA: 0s - loss: 0.0609 116/116 [==============================] - 0s 2ms/step - loss: 0.0607 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0387 39/116 [=========>....................] - ETA: 0s - loss: 0.0764 77/116 [==================>...........] - ETA: 0s - loss: 0.0722 116/116 [==============================] - ETA: 0s - loss: 0.0634 116/116 [==============================] - 0s 1ms/step - loss: 0.0634 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0238 40/116 [=========>....................] - ETA: 0s - loss: 0.0576 78/116 [===================>..........] - ETA: 0s - loss: 0.0707 116/116 [==============================] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0619 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1732 41/116 [=========>....................] - ETA: 0s - loss: 0.0459 80/116 [===================>..........] - ETA: 0s - loss: 0.0524 116/116 [==============================] - 0s 1ms/step - loss: 0.0576 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0909 38/116 [========>.....................] - ETA: 0s - loss: 0.0577 76/116 [==================>...........] - ETA: 0s - loss: 0.0640 114/116 [============================>.] - ETA: 0s - loss: 0.0577 116/116 [==============================] - 0s 1ms/step - loss: 0.0574 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0055 39/116 [=========>....................] - ETA: 0s - loss: 0.0727 78/116 [===================>..........] - ETA: 0s - loss: 0.0556 116/116 [==============================] - ETA: 0s - loss: 0.0549 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0548 40/116 [=========>....................] - ETA: 0s - loss: 0.0504 78/116 [===================>..........] - ETA: 0s - loss: 0.0594 116/116 [==============================] - 0s 1ms/step - loss: 0.0528 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 36/116 [========>.....................] - ETA: 0s - loss: 0.0346 73/116 [=================>............] - ETA: 0s - loss: 0.0463 106/116 [==========================>...] - ETA: 0s - loss: 0.0474 116/116 [==============================] - 0s 1ms/step - loss: 0.0524 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 1, 8 GAN f1 score: 0.800 GAN cohens kappa score: 0.793 -> test with 'LR' LR tn, fp: 277, 11 LR fn, tp: 0, 9 LR f1 score: 0.621 LR cohens kappa score: 0.604 LR average precision score: 0.756 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 1, 8 RF f1 score: 0.842 RF cohens kappa score: 0.837 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 0, 9 KNN f1 score: 0.750 KNN cohens kappa score: 0.740 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 1.5931 38/116 [========>.....................] - ETA: 0s - loss: 0.2292  74/116 [==================>...........] - ETA: 0s - loss: 0.1895 113/116 [============================>.] - ETA: 0s - loss: 0.1564 116/116 [==============================] - 0s 1ms/step - loss: 0.1605 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.3052 39/116 [=========>....................] - ETA: 0s - loss: 0.1323 77/116 [==================>...........] - ETA: 0s - loss: 0.0994 112/116 [===========================>..] - ETA: 0s - loss: 0.0943 116/116 [==============================] - 0s 1ms/step - loss: 0.0920 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0276 41/116 [=========>....................] - ETA: 0s - loss: 0.0667 81/116 [===================>..........] - ETA: 0s - loss: 0.0737 116/116 [==============================] - 0s 1ms/step - loss: 0.0686 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0051 39/116 [=========>....................] - ETA: 0s - loss: 0.0590 77/116 [==================>...........] - ETA: 0s - loss: 0.0602 115/116 [============================>.] - ETA: 0s - loss: 0.0635 116/116 [==============================] - 0s 1ms/step - loss: 0.0634 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0091 40/116 [=========>....................] - ETA: 0s - loss: 0.0508 82/116 [====================>.........] - ETA: 0s - loss: 0.0547 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0742 39/116 [=========>....................] - ETA: 0s - loss: 0.0647 77/116 [==================>...........] - ETA: 0s - loss: 0.0552 115/116 [============================>.] - ETA: 0s - loss: 0.0570 116/116 [==============================] - 0s 1ms/step - loss: 0.0570 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1070 38/116 [========>.....................] - ETA: 0s - loss: 0.0432 70/116 [=================>............] - ETA: 0s - loss: 0.0572 102/116 [=========================>....] - ETA: 0s - loss: 0.0533 116/116 [==============================] - 0s 1ms/step - loss: 0.0542 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0200 36/116 [========>.....................] - ETA: 0s - loss: 0.0559 74/116 [==================>...........] - ETA: 0s - loss: 0.0588 112/116 [===========================>..] - ETA: 0s - loss: 0.0543 116/116 [==============================] - 0s 1ms/step - loss: 0.0529 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0477 40/116 [=========>....................] - ETA: 0s - loss: 0.0377 79/116 [===================>..........] - ETA: 0s - loss: 0.0513 116/116 [==============================] - ETA: 0s - loss: 0.0536 116/116 [==============================] - 0s 1ms/step - loss: 0.0536 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0153 34/116 [=======>......................] - ETA: 0s - loss: 0.0449 71/116 [=================>............] - ETA: 0s - loss: 0.0447 109/116 [===========================>..] - ETA: 0s - loss: 0.0526 116/116 [==============================] - 0s 1ms/step - loss: 0.0526 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 3, 6 GAN f1 score: 0.600 GAN cohens kappa score: 0.586 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.654 LR average precision score: 0.579 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 3, 6 RF f1 score: 0.750 RF cohens kappa score: 0.743 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 0, 9 KNN f1 score: 0.783 KNN cohens kappa score: 0.774 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 5.3343e-04 35/116 [========>.....................] - ETA: 0s - loss: 0.0933  68/116 [================>.............] - ETA: 0s - loss: 0.0703 102/116 [=========================>....] - ETA: 0s - loss: 0.0661 116/116 [==============================] - 0s 1ms/step - loss: 0.0707 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0011 40/116 [=========>....................] - ETA: 0s - loss: 0.0344 73/116 [=================>............] - ETA: 0s - loss: 0.0572 107/116 [==========================>...] - ETA: 0s - loss: 0.0573 116/116 [==============================] - 0s 1ms/step - loss: 0.0614 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0016 39/116 [=========>....................] - ETA: 0s - loss: 0.0683 77/116 [==================>...........] - ETA: 0s - loss: 0.0630 113/116 [============================>.] - ETA: 0s - loss: 0.0616 116/116 [==============================] - 0s 1ms/step - loss: 0.0607 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0035 38/116 [========>.....................] - ETA: 0s - loss: 0.0789 76/116 [==================>...........] - ETA: 0s - loss: 0.0590 115/116 [============================>.] - ETA: 0s - loss: 0.0556 116/116 [==============================] - 0s 1ms/step - loss: 0.0555 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0497 40/116 [=========>....................] - ETA: 0s - loss: 0.0424 79/116 [===================>..........] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0541 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0307 39/116 [=========>....................] - ETA: 0s - loss: 0.0637 77/116 [==================>...........] - ETA: 0s - loss: 0.0617 115/116 [============================>.] - ETA: 0s - loss: 0.0539 116/116 [==============================] - 0s 1ms/step - loss: 0.0538 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0186 39/116 [=========>....................] - ETA: 0s - loss: 0.0785 77/116 [==================>...........] - ETA: 0s - loss: 0.0575 115/116 [============================>.] - ETA: 0s - loss: 0.0513 116/116 [==============================] - 0s 1ms/step - loss: 0.0512 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0309 39/116 [=========>....................] - ETA: 0s - loss: 0.0375 80/116 [===================>..........] - ETA: 0s - loss: 0.0503 114/116 [============================>.] - ETA: 0s - loss: 0.0501 116/116 [==============================] - 0s 1ms/step - loss: 0.0498 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0185 38/116 [========>.....................] - ETA: 0s - loss: 0.0519 77/116 [==================>...........] - ETA: 0s - loss: 0.0509 116/116 [==============================] - 0s 1ms/step - loss: 0.0487 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0045 39/116 [=========>....................] - ETA: 0s - loss: 0.0545 78/116 [===================>..........] - ETA: 0s - loss: 0.0572 116/116 [==============================] - 0s 1ms/step - loss: 0.0474 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 2, 6 GAN f1 score: 0.462 GAN cohens kappa score: 0.441 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 0, 8 LR f1 score: 0.552 LR cohens kappa score: 0.533 LR average precision score: 0.480 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 3, 5 RF f1 score: 0.588 RF cohens kappa score: 0.576 -> test with 'GB' GB tn, fp: 282, 6 GB fn, tp: 3, 5 GB f1 score: 0.526 GB cohens kappa score: 0.511 -> test with 'KNN' KNN tn, fp: 274, 14 KNN fn, tp: 1, 7 KNN f1 score: 0.483 KNN cohens kappa score: 0.462 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 282, 17 LR fn, tp: 2, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.895 average: LR tn, fp: 276.76, 11.24 LR fn, tp: 0.32, 8.48 LR f1 score: 0.601 LR cohens kappa score: 0.584 LR average precision score: 0.691 minimum: LR tn, fp: 271, 6 LR fn, tp: 0, 7 LR f1 score: 0.471 LR cohens kappa score: 0.446 LR average precision score: 0.387 -----[ RF ]----- maximum: RF tn, fp: 288, 8 RF fn, tp: 5, 9 RF f1 score: 0.889 RF cohens kappa score: 0.885 average: RF tn, fp: 285.44, 2.56 RF fn, tp: 2.32, 6.48 RF f1 score: 0.727 RF cohens kappa score: 0.718 minimum: RF tn, fp: 280, 0 RF fn, tp: 0, 4 RF f1 score: 0.455 RF cohens kappa score: 0.434 -----[ GB ]----- maximum: GB tn, fp: 288, 8 GB fn, tp: 6, 8 GB f1 score: 0.889 GB cohens kappa score: 0.885 average: GB tn, fp: 285.04, 2.96 GB fn, tp: 2.28, 6.52 GB f1 score: 0.714 GB cohens kappa score: 0.705 minimum: GB tn, fp: 280, 0 GB fn, tp: 0, 3 GB f1 score: 0.300 GB cohens kappa score: 0.276 -----[ KNN ]----- maximum: KNN tn, fp: 287, 15 KNN fn, tp: 3, 9 KNN f1 score: 0.947 KNN cohens kappa score: 0.946 average: KNN tn, fp: 279.0, 9.0 KNN fn, tp: 0.32, 8.48 KNN f1 score: 0.659 KNN cohens kappa score: 0.645 minimum: KNN tn, fp: 273, 1 KNN fn, tp: 0, 6 KNN f1 score: 0.483 KNN cohens kappa score: 0.462 -----[ GAN ]----- maximum: GAN tn, fp: 286, 12 GAN fn, tp: 3, 9 GAN f1 score: 0.842 GAN cohens kappa score: 0.837 average: GAN tn, fp: 281.0, 7.0 GAN fn, tp: 1.52, 7.28 GAN f1 score: 0.637 GAN cohens kappa score: 0.623 minimum: GAN tn, fp: 276, 2 GAN fn, tp: 0, 6 GAN f1 score: 0.462 GAN cohens kappa score: 0.441